sign in sign up
<<
Home , Psamment

Joint proceedings of the 27th Science Society of East and the 6th African Society

Characterization of some of the Miombo Woodlands Ecosystem of Kitonga Forest Reserve, Iringa, Tanzania: Physicochemical properties and classification

H.B., Shelukindo1, B.M., Msanya1, E., Semu1, S.B., Mwango1, P.K.T. Munishi2, and B.R. Singh3

1Department of Soil Science, Faculty of Agriculture, Sokoine University of Agriculture, Box 3010, Chuo Kikuu, Morogoro, Tanzania 2Department of Forest Biology, Faculty of Forestry and Nature Conservation, Sokoine University of Agriculture, Box 3010, Chuo Kikuu, Morogoro, Tanzania 3Department of Plant Science and Environment Studies, Norwegian University of Life Sciences, P.O. Box As- Norway 1 Corresponding author: [email protected]. Tel: +255784413162 (Mobile)

Abstract Understanding the soil types of an area is the basis for sustainable soil use and management. Miombo woodland soils have significant implications in global climate change processes. Few studies have characterized and classified the soils of the miombo woodland ecosystem of Tanzania. The current study was carried out to map and classify soils of the Kitonga Forest Reserve, which is a typical miombo woodland ecosystem, in order to generate relevant information for use and management by stakeholders. The dominant soil types of the miombo woodland ecosystem of Kitonga Forest Reserve were characterized and classified using standard methods. Ten soil profiles were excavated and described using standard methods to represent soils of the mapped area. Standard laboratory soil physical and chemical analyses were carried out to enable classification of the soils. According to the World Reference Base (WRB) for Soil Resources system the soils were classified as , and . In the USDA Soil Taxonomy the soils were classified as and . Different soil types differed in physicochemical properties, hence exhibit differences in their potentials and constraints for management and use. Topographical features played a very important role in soil formation. Sustainable management of miombo woodlands ecosystem soils requires reduced deforestation and reduced land degradation. The information obtained would be useful in planning management strategies of miombo woodlands ecosystem with similar ecological conditions. Key words: Miombo woodlands ecosystem, soil physico-chemical properties, , Kitonga Forest Reserve, Tanzania. Introduction Soils vary greatly across the landscape and are influenced by topographical features. The soils of the miombo woodland ecosystems are important globally in climate change processes (Munishi et al., 2011). However, few studies have characterized and classified the soils in Tanzania and especially those of the miombo woodlands ecosystem (Msanya et al., 2003). In Tanzania, the miombo woodland ecosystem is found, among other places, in the Kitonga Forest Reserve (KFR). Understanding the dominant soil types and characteristics of the miombo woodlands ecosystem soils in Tanzania would facilitate availability of information on potentials and constraints of soils for different management and uses which will contribute to reduced disturbances and land degradation. The miombo woodlands, which cover about 31.62 million hectares or 93% of the total forested land area in Tanzania, are important as they provide diverse ecosystem services which support livelihoods to adjacent communities (FAO, 2009). The major aim of the study was to study the dominant soil types in the miombo woodlands in the KFR with the specific objectives:  to map the soils and their spatial distribution over the study area  to characterize the soils based on physicochemical properties  to classify the soils using the World Reference Base (WRB) for Soil Resource and (FAO, 2006) and the United States Department of Agriculture Soil Taxonomy system (Soil Survey Staff, 2010) Joint proceedings of the 27th Soil Science Society of East Africa and the 6th African Soil Science Society

 to provide data for use by stakeholders in planning sustainable land management in miombo woodlands. Materials and methods Study site The KFR is located in Kilolo District, Iringa Region, on the northern and southern sides of the Iringa- Morogoro road, at 07°35' - 07°43'S; and 37°07' - 37°10'E. The altitude varies from 660- 1880 m above sea level, with rainfall ranging from 540 mm to 900 mm, with a mean of 720 mm. The temperatures range from 13.5 to 24.7 0C, with maximum temperatures in July to October (Shirima et al., 2011). Figure 1 shows the location of the study area. Detailed site characteristics of the study area are presented in Table 1. Methodology Field Methods Using standard procedures (FAO-WRB, 2006); Munsell Color Co., 1992), ten soil profiles were located using the Global Positioning System (GPS) receiver, and were examined, described and samples collected from natural horizons. In each profile pit, disturbed and undisturbed samples were taken from each horizon for physical and chemical analysis in the laboratory.

Joint proceedings of the 27th Soil Science Society of East Africa and the 6th African Soil Science Society

Figure 1: Map showing the study area (Source: Kilolo District Profile, 2010)

Laboratory Methods Physical and chemical analyses were conducted as follows. The bulk density was determined using the core method (Black & Hartge, 1986), and texture was determined by the hydrometer method (Day, 1965). The pH was measured in water and 1 M CaCl2 at a ratio of 1:2.5 soil: water and soil: Joint proceedings of the 27th Soil Science Society of East Africa and the 6th African Soil Science Society

CaCl2, respectively (McLean, 1986). Organic carbon was determined by the wet oxidation method (Nelson & Sommers, 1982) and converted to

Table 1: Salient features of the study area- Kitonga Forest Reserve Altitude Location Profile Slope Land form Slope SMR STR (masl) No. gradient form 831 5 25 Lower slope Straight Thermic 7° 39' 53.68'' S 928 3 15 V- Shaped Concave Acquic Thermic 7° 38' 32.5'' S Valley bottom 980 4 12 Ridge summit Convex Ustic Thermic 7° 39' 45.14'' S (Lower) 1083 2 17 Ridge Middle Straight Ustic Thermic slope 1241 8 10 U- Shaped Concave Acquic Mesic Valley bottom 1258 9 10 Foot slope Straight Ustic Mesic

1320 10 22 Ridge Lower Straight Ustic Mesic 7° 38' 59.93'' S slope 1377 7 25 Ridge Middle Straight Ustic Mesic slope 1548 6 10 U-Shaped Concave Ustic Mesic Valley bottom 1598 36° 10' 30.22'' E 1 1 Ridge Summit Convex Ustic Mesic

SMR= regime STR= soil temperature regime organic matter by multiplying by a factor of 1.724. Total N was determined using the micro-Kjeldahl digestion- distillation method as described by Bremner and Mulvaney (1982). Extractable phosphorus was determined using filtrates extracted by the Bray and Kurtz-1 method (Bray and Kurtz, 1945) and determined by spectrophotometer (Watanabe and Olsen, 1965). The exchangeable bases (Ca2+, Mg2+, Na+ and K+) were determined by atomic absorption spectrophotometer (Thomas, 1982). Soil classification Using field and laboratory data, the soils were classified to tier-2 of the FAO World Reference Base (FAO-WRB, 2006), and to subgroup level of the USDA Soil Taxonomy (Soil Survey Staff, 2010). Results and discussion Physical and chemical properties of the soils Selected physical and chemical properties of the soils are indicated in Table 2. The soils varied in physicochemical properties. They are well drained, dominantly coarse textured and varied from and sandy texture in the surface to sandy loam in the subsurface. The coarse textured soils with more than 65% sand and less than 18% clay have low nutrient fertility status. Vagen and Winowiecki (2013), in their study conducted in Kenya (Dambidolo) and Tanzania (Mbinga), reported differences in nutrient storage capacity of soils due to varying in sand contents. Joint proceedings of the 27th Soil Science Society of East Africa and the 6th African Soil Science Society

According to Baize (1993), EUROCONSULT (1989) and Landon (1991), the majority of soils were grouped as acidic. The soil pH ranged from strongly acid (5.1) to neutral (6.8) with a mean pH of 5.9 which is favorable for the growth of woodlands in mountainous and forest areas. The OC content was rated as very low (0.1%) to very high (4.4%) with mean of (2.6%) (medium). The cation exchange capacity (CEC- NH4OAc) ranged from very low (3 cmol (+)/kg) to medium (18 cmol (+)/kg). Generally, the soils are poor in nutrients. The low nutrient status of the soils across the study area could be attributed to frequent fires and continual deforestation of the miombo woodlands ecosystem. Frost (1996) observed a similar trend in the soils of miombo woodlands in Tabora (Tanzania), which are inherently poor in nutrients but with a wide variation in fertility. Soil mapping units, soil classification and their relationship to topography The detailed classification of soils representative of the mapping units of Kitonga Forest Reserve is shown in Table 3. The soils were classified as Cambisols, and Fluvisols (FAO-WRB, 2006) or Inceptisols and Entisols (USDA Soil Taxonomy). Different soil types were found under specific topographical features. Cambisols (Inceptisols) were found on ridge summit slopes with convex slopes, Fluvisols (Entisols) were found on U and V shaped valley bottoms with concave slopes, and Leptosols were found on ridge middle slopes with straight slopes (c.f Table 1). This explains the contribution of topographical features (landforms) in forming different soil types. The findings agreed with those of Abebayehu (2013) that topographic features affect physical and chemical properties of the soils. Table 4 gives a summary of the mapping units and their areal extent with Cambisols dominating (70%). Joint proceedings of the 27th Soil Science Society of East Africa and the 6th African Soil Science Society

Table 2: Selected physico-chemical properties of soils of Kitonga Forest Reserve Profile No. Horizon Depth (cm) pH % Texture Text. BD % OC %OM % N mg/kg Bases and CEC (cmol(+)/kg H2O CaCl Clay Sand Class g/cc Av. P Ca Mg Na K CEC- 2 NH4OAc 1 Ah 0-15 5.2 4 34.3 9.3 57 SCL 1.08 0.42 0.73 0.03 0.62 0.48 0.5 0.23 0.43 6.6 BA 15- 32 5.46 4.31 34.3 7.3 59 SCL 1.16 0.17 0.29 0.02 0.5 0.53 0.46 0.22 0.36 6 Bw1 32- 57 5. 6 4.7 30.3 6.6 63 SCL 1.04 0.15 0.26 0.01 0.39 0.63 0.45 0.2 0.29 6.6 BW2 57- 80 6.7 6.2 14.3 4.6 81 SL 1.22 1.57 2.72 0.11 28.89 4.96 2.2 0.2 0.36 10.4 2 Ah 0- 10 5.9 4.9 22.3 4.6 73 SCL 1 0.62 1.07 0.06 2.3 1.31 2.95 0.26 0.31 6.4 Bw 10- 25.0 5.2 4.7 10.3 4.6 85 LS 1.1 2 3.46 0.13 9.5 3.04 1.44 0.21 0.27 9 3 Ah 0- 16 5.1 4.4 10.3 4.56 85 LS 1.14 0.4 0.69 0.4 0.5 0.4 1.17 0.16 0.14 5.8 BA 16- 33 5.3 4.4 10.3 2.56 87 LS 1.1 0.2 0.35 0.1 0.17 0.48 1.19 0.17 0.14 4.4 Bw 33- 45 6.4 5.8 10.3 4.56 85 LS 1.11 1.25 2.17 0.1 19 3.42 1.13 0.17 0.46 9 4 Ah 0- 16 5.4 4.6 14.3 6.6 79 SL 1.31 1.25 2.17 0.11 6.7 1.69 2.8 0.19 0.46 10 5 Ah 0- 20 6.8 6.2 24.3 12.6 63 SCL 1.21 4.4 7.62 0.25 3.14 10.7 3 0.33 0.52 24 6 Ah 0- 15 6.2 5.9 26.3 10.6 66.1 SCL 1.23 2.1 3.64 0.17 1.4 5.2 2.4 0.3 0.3 16.6 BA 15- 27 6.2 4.8 20.3 4.6 75.1 SCL 1.31 1.4 2.42 0.08 0.5 2.5 1.3 0.3 0.2 9.4 Bt1 27- 45 6 4.8 24.3 2.6 73.1 SCL 1.3 1.3 2.25 0.05 0.84 2.7 1.3 0.3 0.1 9.2 Bt2 45- 60 5.5 4.4 28.3 4.6 67.1 SCL 1.21 1.17 2.03 0.06 0.84 3 1.6 0.4 0.3 9.4 2BAb 60- 100 5.9 4.4 12.3 8.6 79.1 SL 1.17 1.55 2.68 0.08 19.7 3.4 1.5 0.2 0.2 8.2 7 Ah 0- 17 5.1 4.1 12.3 8.6 79.1 SL 1.21 0.44 0.76 0.03 7.4 2.5 0.9 0.2 0.2 8.6 Bt 17- 35 6.1 4.4 28.3 4.6 67.1 SCL 1.26 1.62 2.81 0.18 1 2.9 1.1 0.7 0.3 13.2 8 Ah 0-19 6 4.2 8.4 4.6 77.1 S 1.09 1.12 1.94 0.1 0.3 1.5 0.6 0.4 0.2 8.4 Bw 19-39 6.9 4.4 6.3 0.6 93.1 S 1.11 0.17 0.29 0.01 5.8 0.7 0.3 0.4 0.2 4 2Bgb1 39-72 6.2 4.5 6.3 0.6 93.1 LS 1.1 0.09 0.16 0.01 2.6 0.6 0.2 0.2 0.1 3 2Bgb2 72- 130 5.4 4.4 10.3 2.6 87.1 LS nd 1.39 2.41 0.07 2.4 0.7 0.8 0.2 0.3 7.4 9 Ah 0- 10 6.1 4.4 10.3 4.6 85.1 LS 1.12 0.4 0.69 0.04 2.1 0.4 0.6 0.2 0.2 4.8 Bw 10- 25.0 5.9 4.2 8.3 2.6 89.1 LS 1.2 0.3 0.52 0.01 0.4 1.5 0.3 0.2 0.2 3.4 BC 25- 45 6.2 4.3 16.3 4.6 79.1 SL 1.2 1.3 2.25 0.08 1.1 1.5 0.6 0.4 0.1 8.6 10 Ah 0- 17 5.1 4.1 12.3 8.6 79.1 SL 1.2 0.44 0.76 0.03 7.4 2.5 0.9 0.2 0.2 8.6 Bt 17-35 6.1 4.4 28.3 4.6 67.1 SCL 1.26 1.62 2.81 0.18 1 2.9 1.1 0.7 0.3 13.2

Joint proceedings of the 27th Soil Science Society of East Africa and the 6th African Soil Science Society

Table 3: Classification of the soils of Kitonga Forest Reserve

FAO- WRB (2006) USDA Soil Taxonomy (Soil Survey Staff, 2010)

Profile No Reference Soil Prefix Qualifier(s) Suffix Tier-2 soil names Order Suborder Greatgroup Subgroup Groups (RSGs) Qualifier(s)

1 Ferralic Ferralic Cambisol (Epidystric, Chromic) Ustept Drystrustept Oxic Dystrustept Epidystric, Chromic

2 Leptosol Cambic Eutric Cambic Leptosol (Eutric) Orthent Ustorthent Lithic Orthent

3 Fluvic, Haplic Dystric Haplic Fluvic, Fluvisol (Dystric) Entisol Psamment Ustipsamment Lithic Ustipsamment

4 Leptosol Cambic Eutric Cambic Leptosol (Eutric) Entisol Orthent Ustorthent Lithic Ustorthent

5 Leptosol Mollic Humic, Eutric Mollic Leptosol (Humic, Eutric) Entisol Orthent Ustorthent Lithic Ustorthent

6 Fluvisol Stagnic, Umbric Endoeutric, Umbric Stagnic Fluvisol (Endoeutric, Entisol Fluvent Usticfluvent Oxyaquic Humic Humic) Usticfluvent

7 Cambisol Ferralic Dystric Ferralic Cambisol (Dystric) Inceptisol Ustept Drystrustept Oxic Dystrustept

8 Fluvisol Fluvic, Stagnic Dystric, Stagnic Fluvic Fluvisol (Dystric, Chromic) Entisol Fluvent Usticfluvent Oxyaquic Chromic Ustifluvents

9 Cambisol Haplic Eutric Haplic Cambisol (Chromic, Eutric) Inceptisol Ustept Drystrustept Typic Dystrustept

10 Cambisol Ferralic Eutric Ferralic Cambisol (Eutric) Inceptisol Ustept Drystrustept Oxic Dystrustept

Joint proceedings of the 27th Soil Science Society of East Africa and the 6th African Soil Science Society

Table 4: Summary of soil mapping units and their areal extent, Kitonga Forest Reserve

Soil mapping units Soil types (FAO-WRB, 2006) Area extent of SMUs % distribution (SMUs) in ha SF Stagnic Fluvisol 4 0.52 HF Haplic Fluvisol 10 1.30 HC Haplic Cambisol 30 3.89 CL Cambic Leptosol 115 14.92 FC Ferralic Cambisol 510 66.15 NR Natural reserve (not described because 102 13.23 of inaccessibility Total area 771 100.00

Conclusion and recommendations Leptosols, Cambisols and Fluvisols were identified as the dominant soil types by the FAO- WRB (2006), which was equivalent to Entisols and Inceptisols in USDA Soil Taxonomy classification. Each dominant was found in specific topographical features, and exhibited with varied physicochemical properties. This implies the need for specific land management and conservation strategies for each soil type. The low levels of nutrient status in the miombo woodlands justifies the need for conservation and management strategies including avoiding fires, grazing, deforestation and cultivation, as adaptation and mitigation measures. Acknowledgements The authors are thankful for the financial support provided by the Climate Change Impacts Adaptation and Mitigation Measures (CCIAM) Project, Sokoine University of Agriculture which enabled us to undertake this study. References Abebayehu, A. (2013). Evaluating organic carbon storage capacity of forest soil: Case study in Kafa Zone Bita District, Southwestern Ethiopia. American Eurasian Journal Agriculture Environmental Science 13(1): 95 – 100. Baize, D. (1993). Soil science analysis. A guide to correct use. John Wiley and Sons Ltd. West Sussex. pp. 192. Black, G.R. & K.H. Hartge 1986. Bulk Density. In (A. Klute, ed.) Methods of Soil Analysis, part 1, 2nd edition, Agronomy Monograph No. 9, pp. 364-376. American Society of Agronomy & Soil Science Society of America, Madison, Wisconsin. Bray, R.H. & L.T. Kurtz 1945. Determination of total, organic and available forms of Phosphorus in soils. Soil Science, 59: 39-45. Bremner, J.M. & C.S. Mulvaney 1982. Total nitrogen. In (L.A. Page, R.H. Miller & D.R. Keeney, eds.) Methods of Soil Analysis, Part 2, 2nd Edition, Agronomy Monograph no. 9, pp. 595-624. American Society of Agronomy, Madison, Wisconsin. Day, P.R. 1965. Particle fractionation and particle size analysis. In (C.A. Black, D.D. Evans, J.L. White, L.E. Ensminger & F.E. Clark, eds.) Methods of Soil Analysis, Part 1, Physical and Mineralogical Methods, pp. 545-566. American Society of Agronomy, Madison, Wisconsin. EUROCONSULT (1989). Agriculture compendium for Rural Development in the Tropics and sub tropics: 3rd revised edition. Elsevier, Amsterdam. Oxford. New York. Tokyo. pp. 740.

Transforming rural livelihoods in Africa: How can land and water management contribute to enhanced food security and address climate change adaptation and mitigation? 20-25 October 2013. Nakuru, Kenya. Joint proceedings of the 27th Soil Science Society of East Africa and the 6th African Soil Science Society

FAO (2009). State of World’s Forests. Food and Agriculture Organization of the United Nations. Rome. pp. 168. FAO-WRB (2006). World Reference Base for soil resource. A framework for international Classification, correlation and communication. World Soil Resources reports 103:145 – 159. Frost, P. (1996). The ecology of Miombo woodlands. The Miombo in transition: woodlands and welfare in Africa. B. M. Campbell. Bogor, Indonesia, Center for International Forestry Research: 11-55. Landon, J. R. (1991) (editor). Booker Tropical Soil Manual. A handbook for soil survey and agricultural land evaluation in the tropics and subtropics. Longman Scientific & Technical Publishers, Essex. pp. 474. McLean, E.O. 1986. Soil pH and lime requirement. In (A.L. Page, R.H. Miller & D.R. Keeny, eds.) Methods of Soil Analysis, part 2, Chemical and Mineralogical Properties, 2nd Edition. Agronomy Monograph no. 9, pp. 199-223. American Society of Agronomy & Soil Science Society of America, Madison, Wisconsin. Msanya, B. M., Kaaya, A. K., Araki, S., Otsuka, H. and Nyadzi, G. I. (2003). Pedological Characteristics, General Fertility and Classification of Some Benchmark Soils of Morogoro District, Tanzania; African Journal of Science and Technology (AJST) Science and Engineering Series 4 (2): 101-112. Munishi, P. K. T., Temu, R. P. C. and Soka, G. (2011). Plant Communities and tree species associations in a Miombo ecosystem in the Lake Rukwa basin, Southern Tanzania: Implications for conservation. Journal of Ecology and the Natural Environment 3(2): 63 – 71. Munsell Color Company 1992. Munsell Charts. Baltimore, Maryland. Nelson, D.W. and L.E. Sommers 1982. Total carbon, organic carbon and organic matter. In (L.A. Page, R.H. Miller & D.R. Keeny, eds.) Methods of Soil Analysis, part 2, 2nd edition, Agronomy Monograph no. 9, pp. 539-579. American Society of Agronomy & Soil Science Society of America, Madison, Wisconsin. Shirima, D. D., Munishi, P. K. T., Lewis, S. L., Burgess, N. D., Marshall, A. R., Balmford, A., Swetnam, R. D. and Zahabu, E. M. (2011). Carbon storage, structure and composition of miombo woodlands in Tanzania’s Eastern Arc Mountains. African Journal of Ecology 49: 332 – 342. Soil Survey Staff (2010). Keys to Soil Taxonomy. United State Department of Agriculture. Eleventh edition. Natural Resource Conservation Service. pp. 346. Thomas, G.W. 1982. Exchangeable cations. In (L.A. Page, R.H. Miller & D.R. Keeny, eds.) Methods of Soil Analysis, part 2, 2nd edition, Chemical and Mineralogical Properties, Agronomy Monograph No. 9, pp. 595-624. American Society of Agronomy & Soil Science Society of America, Madison, Wisconsin. Tor-Gunnar, V. and L.A. Winowiecki. (2013).Mapping of soil organic carbon stocks for spatially explicit assessments of climate change mitigation potential. Environmental Research Letters 8: 9 – 10. Watanabe, F.S. and S.R. Olsen 1965. Test of an ascorbic acid method for determining phosphorus in water and NaHCO3 extracts from Soil. Soil Science Society of America Proceedings, 29: 677-678.

9 Transforming rural livelihoods in Africa: How can land and water management contribute to enhanced food security and address climate change adaptation and mitigation? Nakuru, Kenya. 20-25 October 2013